EDAForge: Automatic Exploratory Data Analysis
Automatically performs exploratory data analysis (EDA)
for tabular datasets, including data summaries, missing value
analysis, descriptive statistics, visualizations, correlation
analysis, outlier detection, and automated report generation.
The package provides a streamlined workflow for rapid data
exploration and produces publication-ready tables and graphics.
For methodological details see Tukey (1977,
ISBN:9780201076165), Pearson (1895)
<doi:10.1098/rspl.1895.0041>, and Wickham (2014)
<doi:10.18637/jss.v059.i10>.
| Version: |
0.1.1 |
| Depends: |
R (≥ 4.2) |
| Imports: |
e1071, rlang, dplyr, ggplot2, tidyr, psych, factoextra, openxlsx, GGally, visdat, igraph |
| Suggests: |
knitr, mice, rmarkdown, testthat (≥ 3.0.0), tibble |
| Published: |
2026-08-08 |
| DOI: |
10.32614/CRAN.package.EDAForge (may not be active yet) |
| Author: |
Vinodhkumar Obli Rajendran [aut, cre],
Keerthi Aaradhana [aut] |
| Maintainer: |
Vinodhkumar Obli Rajendran <vinodhkumar.rajendran at gmail.com> |
| BugReports: |
https://github.com/vinodhpmd/EDAForge/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/vinodhpmd/EDAForge |
| NeedsCompilation: |
no |
| Citation: |
EDAForge citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
EDAForge results |
Documentation:
Downloads:
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